Design-based research studies are conducted as iterative implementation-analysis-modification cycles, in which emerging theoretical models and pedagogically plausible activities are reciprocally tuned toward each other as a means of investigating conjectures pertaining to mechanisms underlying content teaching and learning. Yet this approach, even when resulting in empirically effective educational products, remains under-conceptualized as long as researchers cannot be explicit about their craft and specifically how data analyses inform design decisions. Consequentially, design decisions may appear arbitrary, design methodology is insufficiently documented for broad dissemination, and design practice is inadequately conversant with learning-sciences perspectives. One reason for this apparent under-theorizing, I propose, is that designers do not have appropriate constructs to formulate and reflect on their own intuitive responses to students’ observed interactions with the media under development. Recent socio-cultural explication of epistemic artifacts as semiotic means for mathematical learners to objectify presymbolic notions (e.g., Radford, Mathematical Thinking and Learning 5(1): 37–70, 2003) may offer design-based researchers intellectual perspectives and analytic tools for theorizing design improvements as responses to participants’ compromised attempts to build and communicate meaning with available media. By explaining these media as potential semiotic means for students to objectify their emerging understandings of mathematical ideas, designers, reciprocally, create semiotic means to objectify their own intuitive design decisions, as they build and improve these media. Examining three case studies of undergraduate students reasoning about a simple probability situation (binomial), I demonstrate how the semiotic approach illuminates the process and content of student reasoning and, so doing, explicates and possibly enhances design-based research methodology.

The concept of autonomy is of crucial importance for understanding life and cognition. Whereas cellular and organismic autonomy is based in the self-production of the material infrastructure sustaining the existence of living beings as such, we are interested in how biological autonomy can be expanded into forms of autonomous agency, where autonomy as a form of organization is extended into the behaviour of an agent in interaction with its environment (and not its material self-production) In this thesis, we focus on the development of operational models of sensorimotor agency, exploring the construction of a domain of interactions creating a dynamical interface between agent and environment. We present two main contributions to the study of autonomous agency: First, we contribute to the development of a modelling route for testing, comparing and validating hypotheses about neurocognitive autonomy. Through the design and analysis of specific neurodynamical models embedded in robotic agents, we explore how an agent is constituted in a sensorimotor space as an autonomous entity able to adaptively sustain its own organization. Using two simulation models and different dynamical analysis and measurement of complex patterns in their behaviour, we are able to tackle some theoretical obstacles preventing the understanding of sensorimotor autonomy, and to generate new predictions about the nature of autonomous agency in the neurocognitive domain. Second, we explore the extension of sensorimotor forms of autonomy into the social realm. We analyse two cases from an experimental perspective: the constitution of a collective subject in a sensorimotor social interactive task, and the emergence of an autonomous social identity in a large-scale technologically-mediated social system. Through the analysis of coordination mechanisms and emergent complex patterns, we are able to gather experimental evidence indicating that in some cases social autonomy might emerge based on mechanisms of coordinated sensorimotor activity and interaction, constituting forms of collective autonomous agency.

Neuroscience techniques provide an open window previously unavailable to the origin of thoughts and actions in children. Developmental cognitive neuroscience is booming, and knowledge from human brain mapping is finding its way into education and pediatric practice. Promises of application in developmental cognitive neuroscience rests however on better theory-guided data interpretation. Massive amounts of neuroimaging data from children are being processed, yet published studies often do not frame their work within developmental models – in detriment, we believe, to progress in this field. Here we describe some core challenges in interpreting the data from developmental cognitive neuroscience, and advocate the use of constructivist developmental theories of human cognition with a neuroscience interpretation.

The article considers the complexities of thinking about the computer as a model of the mind. It examines the computer as being a model of the brain in several very different senses of “model‘. On the one hand the basic architecture of the first modern stored-program computers was „modeled on“ the brain by John von Neumann. Von Neumann also sought to build a mathematical model of the biological brain as a complex system. A similar but different approach to modeling the brain was taken by Alan Turing, who on the one hand believed that the mind simply was a universal computer, and who sought to show how brain-like networks could self-organize into Universal Turing Machines. And on the other hand, Turing saw the computer as the universal machine that could simulate any other machine, and thus any particular human skill and thereby could simulate human intelligence. This leads to a discussion of the nature of “simulation” and its relation to models and modeling. The article applies this analysis to a written correspondence between Ashby and Turing in which Turing urges Ashby to simulate his cybernetic Homeostat device on the ACE computer, rather than build a special machine.

Excerpt: The purpose of this essay is to clarify some of the important senses in which the relationship between the brain and the computer might be considered as one of “modeling.” It also considers the meaning of “simulation” in the relationships between models, computers and brains. While there has been a fairly broad literature emerging on models and simulations in science, these have primarily focused on the physical sciences, rather than the mind and brain. And while the cognitive sciences have often invoked concepts of modeling and simulation, they have been frustratingly inconsistent in their use of these terms, and the implicit relations to their scientific roles. My approach is to consider the early convolution of brain models and computational models in cybernetics, with the aim of clarifying their significance for more current debates in the cognitive sciences. It is my belief that clarifying the historical senses in which the brain and computer serve as models of each other in the historical period prior to the birth of AI and cognitive science is a crucial task for an archeology of AI and the history of cognitive science.

This dissertation reconsiders the nature of scientific models through an historical study of the development of electronic models of the brain by Cybernetics researchers in the 1940s. By examining how these unique models were used in the brain sciences, it develops the concept of a “working model” for the brain sciences. Working models differ from theoretical models in that they are subject to manipulation and interactive experimentation, i.e., they are themselves objects of study and part of material culture. While these electronic brains are often disparaged by historians as toys and publicity stunts, I argue that they mediated between physiological theories of neurons and psychological theories of behavior so as to leverage their compelling material performances against the lack of observational data and sparse theoretical connections between neurology and psychology. I further argue that working models might be used by cognitive science to better understand how the brain develops performative representations of the world.

This paper aims at shedding light on what students can “construct” when they learn science and how this construction process may be supported. Constructivism is a pluralist theory of science education. As a consequence, I support, there are several points of view concerning this construction process. Firstly, I stress that constructivism is rooted in two fields, psychology of cognitive development and epistemology, which leads to two ways of describing the construction process: either as a process of enrichment and/or reorganization of the cognitive structures at the mental level, or as a process of building or development of models or theories at the symbolic level. Secondly, I argue that the usual distinction between “personal constructivism” (PC) and “social constructivism” (SC) originates in a difference of model of reference: the one of PC is Piaget’s description of “spontaneous” concepts, assumed to be constructed by students on their own when interacting with their material environment, the one of SC is Vygotsky’s description of scientific concepts, assumed to be introduced by the teacher by means of verbal communication. Thirdly, I support the idea that, within SC, there are in fact two trends: one, in line with Piaget’s work, demonstrates how cooperation among students affects the development of each individual’s cognitive structures; the other, in line with Vygotsky’s work, claims that students can understand and master new models only if they are introduced to the scientific culture by their teacher. Fourthly, I draw attention to the process of “problem construction” identified by some French authors. Finally, I advocate for an integrated approach in science education, taking into account all the facets of science learning and teaching mentioned above and emphasizing their differences as well as their interrelations. Some suggestions intended to improve the efficiency of science teaching are made.

Key words: science learning science teaching, personal constructivism, social constructivism, cooperation, enculturation, problem construction.

Compared with traditional theories, systems theory presents a deviation. It replaces causal explanation by functional explanation. This paper shows what scandalon is inherent in this substitution and elucidates some models (self-organization, dance, non-triviality, structural coupling) which put the explanatory principle to work. The paper concludes by showing how systems theory aims at a general concept of communication that not only means a passing on of knowledge but above all the tracing of ignorance. Overall, systems theory is presented as a joker dealing with the paradox that the system is never identical to itself as soon as it is considered as a function of itself and its environment. The system has to withdraw into the function it is a function of in order to enfold this paradox.

In the paper we maintain that one way to phrase the title question is to look for the introduction of new media for the distribution of communication as chocks forcing society to develop new structures to both reject and accept possible communication. We develop a kind of media archeology by checking this thesis in the four cases of language, writing, the printing press, and the computer, respectively. We show that four models, the ethnological, the ontological, the functional, and the ecological, help to hold society together by precisely asking the question of how it holds together. The paper is relevant for constructivist approaches because it shows the culture forms that different societies rely on to construct themselves.

The classical formulation of the object of ethics refers to a knowledge of the rules of the adaptation of the human species to their natural environments, to normative expectations supposed in the others and to the biographical evolution of the self. Accordingly, a doctrine of the duties was edified on three pillars, embracing a reference to the duties towards nature, towards the others and towards oneself. Notwithstanding the fact that human action obeys to a variety of factors including bio-physiological conditions and the dimensions of the social environment, ancient and modern metaphysical models of ethics favored the commendatory discourse about the predicates “right” and “wrong,” concurring to ultimate goals. The ethical discussions consisted chiefly in the investigation of the adequacy of the subordinate goals to the final ends of the human action or in the treatment of the metaphysical questions related to free will or determinism, the opposition of the intentionality of the voluntary conduct of man to the mechanical or quasi-mechanical responses of the inferior organisms or machines. From a “second order” approach to the ethical action and imperatives, I propose with this book a critical analysis of the metaphysical and the Kantian ethics. Relevance: In “Ethics and Second-Order Cybernetics” (1992) Heinz von Foerster referred the importance of the application of his notion of “second-order cybernetics” to ethics and moral reasoning. Initially, second-order cybernetics intended an epistemological discussion of recursive operations in non-trivial machines, which were able to include in their evolving states their own self-awareness in observations. The application of his views to ethics entails new challenges. After H. von Foerster essay, what I mean with “second-order ethics is an attempt to identify the advantages of the adoption of his proposal, some consequences in the therapeutically field and lines for new developments.

Key words: Ethics, moral discourse, commendations, second-order cybernetics, observer, objectivity